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WIREs Comput Mol Sci
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Integrative approaches in HIV ‐1 non‐nucleoside reverse transcriptase inhibitor design

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The design of inhibitors for human immunodeficiency virus type‐1 reverse transcriptase (HIV‐1 RT) is one of the most successful approaches for the treatment of HIV infections. Among the HIV‐1 RT inhibitors, non‐nucleoside reverse transcriptase inhibitors (NNRTIs) constitute a prominent drug class, which includes nevirapine, delavirdine, efavirenz, etravirine, and rilpivirine approved for clinical use. However, the efficiency of many of these drugs has been undermined by drug‐resistant variants of HIV‐1 RT, and it therefore becomes inevitable to design novel drugs to cope with resistance. Here, we discuss various drug design strategies, which include traditional medicinal chemistry, computational chemistry, and chemical biology approaches. In particular, computational modeling approaches, including machine learning, empirical descriptors‐based, force‐field, ab initio, and hybrid quantum mechanics/molecular mechanics‐based methods are discussed in detail. We foresee that these methods will have a major impact on efforts to guide the design and discovery of the next generation of NNRTIs that combat RT multidrug resistance.

HIV‐1 reverse transcriptase (RT) and ligand binding domains with the approved drugs: (a) Three‐dimensional structure of HIV‐1 RT (p66/p51) in complex with nucleic acid; (b) Ligand binding domains include NRTI (blue surface), NNRTI binding pocket (green surface), and 3′end of the primer ds DNA (cartoon representation); (c) Binding mode of approved drugs nevirapine (maroon), efavirenz (cyan), and rilpivirine (green), with important amino acid residues in the binding pocket and schematic representation of ligand ‘pharmacophore’ models shown. The figures were created using the PyMOL version 1.7.
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Illustration of the HIV‐1 replication cycle. The key steps of the replication cycle are binding, fusion (FIs), reverse transcription (NRTIs and NNRTIs), integration (InSTIs), replication, assembly (PIs), budding, and release. The drug targets are highlighted in blue and the corresponding drug classes are in red.
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The three‐dimensional structure of HIV‐1 reverse transcription (RT) in complex with a 33 nucleotide pseudoknot RNA aptamer (pink cartoon). The non‐nucleoside reverse transcriptase inhibitor (NNRTI) binding site is highlighted by the green space‐filling model. The figure was adopted from Jaeger et al. (PDB ID: 1HUV) and created using the PyMOL version 1.7.
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(a) Protein fragmentation scheme. The protein is cut at the peptide bond, and the capping groups, namely –NH–CH3 and –CO–CH3, are added. The calculations are carried out for the capped residues and also for the caps. (b) Illustration of the hybrid quantum mechanics/molecular mechanics (QM/MM) strategy in the protein–ligand complex. The yellow region (ligand and part of active site residues) is modeled with quantum mechanical methods, and the surrounding rest of the system is treated using molecular mechanics or force fields.
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The structure of NNRTIs (see text for detail). The 2D‐diagram of protein–ligand interactions was generated with LigPlot+ (version 1.4.5).
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The ‘common‐structural‐features’ strategy of NNRTI design (see text for detail).
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Schematic representation of accuracy and efficiency of various computational chemistry methods.
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Schematic representation of bioisosterism and molecular hybridization approaches in NNRTI design.
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Overlay of crystal structures of NNRTI drugs. The number of overlaid structures (N) is given below each name, and the number of rotatable (nRotB) bonds is shown below each structure. Bottom right: Correlation between the nRotB and drug efficacy for RT mutant strains (primary Y‐axis, blue dots) and binding affinity for WT RT/mutants (secondary Y‐axis, red dots) is shown (see text for detail). pIC50 values for the five approved drugs were retrieved from PDBBind for WT and mutant RTs; average values are plotted in the figure.
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Integrated approaches in design and lead optimization of potent NNRTIs.
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